Coupled autoregressive active inference agents for control of multi-joint dynamical systems

Tim N. Nisslbeck; Wouter M. Kouw

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arXiv · 2410.10415

Coupled autoregressive active inference agents for control of multi-joint dynamical systems

Tim N. Nisslbeck·Wouter M. Kouw

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Abstract

We propose an active inference agent to identify and control a mechanical system with multiple bodies connected by joints. This agent is constructed from multiple scalar autoregressive model-based agents, coupled together by virtue of sharing memories. Each subagent infers parameters through Bayesian filtering and controls by minimizing expected free energy over a finite time horizon. We demonstrate that a coupled agent of this kind is able to learn the dynamics of a double mass-spring-damper system, and drive it to a desired position through a balance of explorative and exploitative actions. It outperforms the uncoupled subagents in terms of surprise and goal alignment.

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BibTeX RIS

Tim N. Nisslbeck, Wouter M. Kouw. 2024-10-14. Coupled autoregressive active inference agents for control of multi-joint dynamical systems. https://arxiv.org/abs/2410.10415

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